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Selected Engineering Applications of Gradient Free Optimisation Using Cuckoo Search and Proper Orthogonal Decomposition

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Abstract

This paper discusses some engineering applications of gradient free optimisation techniques. This is achieved using the development of the cuckoo search algorithm as a case study. The motivations behind using gradient free algorithms are discussed and illustrated using two specific practical examples. The first involves aerofoil shape optimisation, where it is shown that a modified cuckoo search algorithm performs well when applied both to aerofoil inverse design and aerofoil shape optimisation. This example is then used to discuss the use of reduced order modeling to decrease the computational cost of the optimisation process. We discuss which reduced order modeling techniques based on proper orthogonal decomposition are suitable for these optimisation applications. The second example is that of co-volume mesh optimisation, where it is shown that a modified cuckoo search can significantly outperform alternative non-optimisation and gradient based techniques. We conclude by discussing a number of remaining difficulties which may deter engineers from using gradient free techniques, and suggest ways in which these may be alleviated.

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References

  1. Alonso D, Velazquez A, Vega J (2009) A method to generate computationally efficient reduced order models. Comput Methods Appl Mech Eng 198:2683–2691

    Article  MathSciNet  MATH  Google Scholar 

  2. Anttonen JSR, King PI, Beran PS (2003) POD-based reduced-order models with deforming grids. Math Comput Model 38:41–62

    Article  MathSciNet  MATH  Google Scholar 

  3. Anttonen JSR, King PI, Beran PS (2005) Applications of multi-POD to a pitching and plunging airfoil. Math Comput Model 42:245–259

    Article  MathSciNet  MATH  Google Scholar 

  4. Barone MF, Kalashnikova I, Segalman DJ, Thornquist HK (2009) Stable Galerkin reduced order models for linearized compressible flow. J Comput Phys 228:1932–1946

    Article  MathSciNet  MATH  Google Scholar 

  5. Barrett TR, Bressloff NW, Keane AJ (2006) Airfoil design and optimization using multi-fidelity analysis and embedded inverse design. In: 47th AIAA/ASME/ASCE/AHS/ASC structures, structural dynamics and materials conference, pp 1–21

    Google Scholar 

  6. Bergmann M, Cordier L (2008) Optimal control of the cylinder wake in the laminar regime by trust-region methods and POD reduced-order models. J Comput Phys 227:7813–7840

    Article  MathSciNet  MATH  Google Scholar 

  7. Bhargava V, Fateen S, Bonilla-Petriciolet A (2013) Cuckoo search: a new nature-inspired optimization method for phase equilibrium calculations. Fluid Phase Equilib 337(0):191–200. doi:10.1016/j.fluid.2012.09.018

    Article  Google Scholar 

  8. Bouhoubeiny E, Druault P (2009) Note on the POD-based time interpolation from successive PIV images. C R, Méc 337:776–780

    Article  MATH  Google Scholar 

  9. Bratton D, Kennedy J (2007) Defining a standard for particle swarm optimization. In: Swarm intelligence symposium, SIS’2007. IEEE Press, New York, pp 120–127. doi:10.1109/SIS.2007.368035

    Chapter  Google Scholar 

  10. Brits R, Engelbrecht AP, van den Bergh F (2007) Locating multiple optima using particle swarm optimization. Appl Math Comput 189:1859–1883

    Article  MathSciNet  MATH  Google Scholar 

  11. Burkardt J, Gunzburger M, Lee HC (2006) POD and CVT-based reduced-order modeling of Navier–Stokes flows. Comput Methods Appl Mech Eng 196:337–355

    Article  MathSciNet  MATH  Google Scholar 

  12. Chaiyaratana N, Zalzala A (1997) Recent developments in evolutionary and genetic algorithms: theory and applications. In: Second international conference on Genetic algorithms in engineering systems: innovations and applications, GALESIA’97, vol 446, pp 270–277. doi:10.1049/cp:19971192

    Google Scholar 

  13. Choudhary K, Purohit GN (2011) A new testing approach using cuckoo search to achieve multi-objective genetic algorithm. J Comput 3(4):117–119

    Google Scholar 

  14. Civicioglu P, Besdok E (2013) A conceptual comparison of the cuckoo-search, particle swarm optimization, differential evolution and artificial bee colony algorithms. Artif Intell Rev 39(4):315–346. doi:10.1007/s10462-011-9276-0

    Article  Google Scholar 

  15. Das S, Suganthan P (2011) Differential evolution: a survey of the state-of-the-art. IEEE Trans Evol Comput 15(1):4–31. doi:10.1109/TEVC.2010.2059031

    Article  Google Scholar 

  16. Degroote J, Vierendeels J, Willcox K (2010) Interpolation among reduced-order matrices to obtain parameterized models for design, optimization and probabilistic analysis. Int J Numer Methods Fluids 63:207–230

    MathSciNet  MATH  Google Scholar 

  17. Diez M, Peri D (2010) Robust optimization for ship conceptual design. Ocean Eng 37(11–12):966–977. 10.1016/j.oceaneng.2010.03.010

    Article  Google Scholar 

  18. Du MFQ, Gunzburger M (1999) Centroidal Voronoi tessellations: applications and algorithms. SIAM Rev 41:637–676

    Article  MathSciNet  MATH  Google Scholar 

  19. Eberhart RC, Shi Y (2001) Particle swarm optimization: developments, applications and resources. In: Proceedings of the 2001 congress on evolutionary computation, vol 1, pp 81–86. doi:10.1109/CEC.2001.934374

    Google Scholar 

  20. Eppstein D, Sullivan JM, Üngör A (2004) Tiling space and slabs with acute tetrahedra. Comput Geom 27:237–255

    Article  MathSciNet  MATH  Google Scholar 

  21. Fang F, Pain C, Navon I, Gorman G, Piggott M, Allison P, Ferrell P, Goddard A (2009) A POD reduced order unstructured mesh ocean modelling method for moderate Reynolds number flows. Ocean Model 28:127–136

    Article  Google Scholar 

  22. Fang F, Pain CC, Navon IM, Piggott MD, Gorman GJ, Farrell PE, Allison PA, Goddard AJH (2009) A POD reduced-order 4D-Var adaptive mesh ocean modelling approach. Int J Numer Methods Fluids 60:709–732

    Article  MathSciNet  MATH  Google Scholar 

  23. Ferziger J, Perić M (2002) Computational methods for fluid dynamics, 3rd edn. Springer, Berlin

    Book  MATH  Google Scholar 

  24. Freitag LA, Plassmann P (2000) Local optimization-based simplicial mesh untangling and improvement. Int J Numer Methods Eng 49:109–125

    Article  MATH  Google Scholar 

  25. Gandomi A, Yang XS, Alavi A (2013) Cuckoo search algorithm: a metaheuristic approach to solve structural optimization problems. Eng Comput 29:17–35. doi:10.1007/s00366-011-0241-y

    Article  Google Scholar 

  26. Gandomi AH, Talatahari S, Yang XS, Deb S (2012) Design optimization of truss structures using cuckoo search algorithm. In: The structural design of tall and special buildings. doi:10.1002/tal1033

    Google Scholar 

  27. Ghodrati A, Lotfi S (2012) A hybrid CS/PSO algorithm for global optimization. In: Pan JS, Chen SM, Nguyen N (eds) Intelligent information and database systems. Lecture notes in computer science, vol 7198. Springer, Berlin, pp 89–98. doi:10.1007/978-3-642-28493-9_11

    Chapter  Google Scholar 

  28. Giannakoglou KC (2002) Design of optimal aerodynamic shapes using stochastic optimization methods and computational intelligence. Prog Aerosp Sci 38:43–76

    Article  Google Scholar 

  29. Giannakoglou KC, Papadimitriou DI, Kampolis IC (2006) Aerodynamic shape design using evolutionary algorithms and new gradient-assisted metamodels. Comput Methods Appl Mech Eng 195:6312–6329

    Article  MATH  Google Scholar 

  30. Gilliam X, Dunyak JP, Smith DA, Wu F (2004) Using projection pursuit and proper orthogonal decomposition to identify independent flow mechanisms. J Wind Eng Ind Aerodyn 92:53–69

    Article  Google Scholar 

  31. Giveki D, Salimi H, Bahmanyar G, Khademian Y (2012) Automatic detection of diabetes diagnosis using feature weighted support vector machines based on mutual information and modified cuckoo search. arXiv:1201.2173

  32. Harbeck M, Jameson A (2005) Exploring the limits of shock-free transonic airfoil design. In: AIAA 43rd aerospace sciences meeting and exhibition

    Google Scholar 

  33. Harlow FH, Welch JE (1965) Numerical calculation of time-dependent viscous incompressible flow of fluid with free surface. Phys Fluids 8:2182–2189

    Article  MATH  Google Scholar 

  34. Holmes P, Lumley J, Berkooz G (1996) Turbulence, coherent structures, dynamical systems and symmetry. Cambridge University Press, Cambridge

    Book  MATH  Google Scholar 

  35. Inc (TM) (2009) MATLAB version 7.8.0

  36. Jameson A (2004) Efficient aerodynamic shape optimization. In: 10th AIAA/ISSMO multidisciplinary analysis and optimization conference

    Google Scholar 

  37. Jameson A, Alonso J, Reuther J, Martinelli L, Vassberg JC (1998) Aerodynamic shape optimization techniques based on control theory. In: Control theory, CIME (International Mathematical Summer School), pp 21–27

    Google Scholar 

  38. Kaveh A, Bakhshpoori T (2011) Optimum design of steel frames using cuckoo search algorithm with lévy flights. In: The structural design of tall and special buildings. doi:10.1002/tal.754

    Google Scholar 

  39. Kaveh A, Bakhshpoori T, Ashoory M (2012) An efficient optimization procedure based on cuckoo search algorithm for practical design of steel structures. Int J Optim Civ Eng 2:1–14

    Google Scholar 

  40. Kerschen G, Golinval JC, Vakakis AF, Bergman LA (2005) The method of proper orthogonal decomposition for dynamical characterization and order reduction of mechanical systems: an overview. Nonlinear Dyn 41:147–169

    Article  MathSciNet  MATH  Google Scholar 

  41. Kulfan BM, Bussoletti JE (2006) “Fundamental” parametric geometry representations for aircraft component shapes. In: 11th AIAA/ISSMO multidisciplinary analysis and optimization conference. AIAA paper 2006-6948

    Google Scholar 

  42. Lagarias JC, Reeds JA, Wright MH, Wright PE (1998) Convergence properties of the Nelder–Mead simplex method in low dimensions. SIAM J Optim 9:112–147

    Article  MathSciNet  MATH  Google Scholar 

  43. Ledger PD, Peraire J, Morgan K, Hassan O, Weatherill NP (2004) Parameterised electromagnetic scattering solutions for a range of incident wave angles. Comput Methods Appl Mech Eng 193:3587–3605

    Article  MATH  Google Scholar 

  44. Liakopoulos PIK, Kampolis IC, Giannakoglou KC (2008) Grid enabled, hierarchical distributed metamodel-assisted evolutionary algorithms for aerodynamic shape optimization. Future Gener Comput Syst 24:701–708

    Article  Google Scholar 

  45. Lieu T, Farhat C, Lesoinne M (2006) Reduced-order fluid/structure modeling of a complete aircraft configuration. Comput Methods Appl Mech Eng 195:5730–5742

    Article  MATH  Google Scholar 

  46. Lin JH, Lee HC (2012) Emotional chaotic cuckoo search for the reconstruction of chaotic dynamics. In: Mastorakis N, Mladenov V, Bojkovic Z (eds) Latest advances in systems science & computational intelligence. WSEAS Press, Athens

    Google Scholar 

  47. Lloyd S (1982) Least square quantization in the PCM. IEEE Trans Inf Theory 28:129–137

    Article  MathSciNet  MATH  Google Scholar 

  48. Lucia DJ, Beran PS (2003) Projection methods for reduced order models of compressible flows. J Comput Phys 188:252–280

    Article  MathSciNet  MATH  Google Scholar 

  49. Ly HV, Tran HT (2001) Modeling and control of physical processes using proper orthogonal decomposition. Math Comput Model 33:223–236

    Article  MATH  Google Scholar 

  50. Mackman TJ, Allen CB (2010) Investigation of an adaptive sampling method for data interpolation using radial basis functions. Int J Numer Methods Eng 83:915–938

    MATH  Google Scholar 

  51. Marsden AL, Wang M, Dennis JE Jr., Moin P (2004) Suppression of vortex-shedding noise via derivative-free shape optimization. Phys Fluids 16(10):L83

    Article  Google Scholar 

  52. Mifsud MJ, Shaw ST, MacManus DG (2010) A high-fidelity low-cost aerodynamic model using proper orthogonal decomposition. Int J Numer Methods Fluids 63:468–494

    MATH  Google Scholar 

  53. Mitchell M (1999) An introduction to genetic algorithms, 6th edn. MIT Press, Cambridge

    Google Scholar 

  54. Morgan K, Hassan O, Peraire J (1994) An unstructured grid algorithm for the solution of Maxwell’s equations in the time domain. Int J Numer Methods Fluids 19:849–863

    Article  MATH  Google Scholar 

  55. Morgan K, Hassan O, Peraire J (1996) A time domain unstructured grid approach to the simulation of electromagnetic scattering in piecewise homogeneous media. Comput Methods Appl Mech Eng 134:17–36

    Article  MATH  Google Scholar 

  56. Morgan K, Peraire J, Peiro J (1992) Unstructured grid methods for compressible flows. In: Report 787: Special course on unstructured grid methods for advection dominated flows. AGARD, Paris, pp 1–39

    Google Scholar 

  57. My-Ha D, Lim K, Khoo B, Willcox K (2007) Real–time optimization using proper orthogonal decomposition: free surface shape prediction due to underwater bubble dynamics. Comput Fluids 36:499–512

    Article  MATH  Google Scholar 

  58. Natarajan A, Subramanian S (2012) Bloom filter optimization using cuckoo search. In: Proceedings of the 2012 international conference on computer communication and informatics, Coimbatore, India

    Google Scholar 

  59. Naylor DJ (1999) Filling space with tetrahedra. Int J Numer Methods Eng 44:1383–1395

    Article  MathSciNet  MATH  Google Scholar 

  60. Nelder JA, Mead R (1965) A simplex method for function minimization. Comput J 7(4):308–313. doi:10.1093/comjnl/7.4.308. http://comjnl.oxfordjournals.org/content/7/4/308.abstract

    Article  MATH  Google Scholar 

  61. Ohtake Y, Belyaev A, Bogaevski I (2001) Mesh regularization and adaptive smoothing. Comput Aided Des 33:789–800

    Article  Google Scholar 

  62. Pavlyukevich I (2007) Lévy flights, non-local search and simulated annealing. J Comput Phys 226:1830–1844

    Article  MathSciNet  MATH  Google Scholar 

  63. Payne RB, Sorenson MD, Kiltz K (2005) The cuckoos. Oxford University Press, London

    Google Scholar 

  64. Periaux J, Lee DS, Gonzalez LF, Srinivas K (2009) Fast reconstruction of aerodynamic shapes using evolutionary algorithms and virtual Nash strategies in a CFD design environment. J Comput Appl Math 232:61–71

    Article  MATH  Google Scholar 

  65. Pettit CL, Beran PS (2002) Application of proper orthogonal decomposition to the discrete Euler equations. Int J Numer Methods Eng 55:479–497

    Article  MATH  Google Scholar 

  66. Praveen C, Duvigneau R (2009) Low cost PSO using metamodels and inexact pre-evaluation: application to aerodynamic shape design. Comput Methods Appl Mech Eng 198:1087–1096

    Article  MATH  Google Scholar 

  67. Pritchard R, Hassan O, Morgan K (2011) An efficient marker and cell solver for unstructured hybrid meshes. In: Wall WA, Gravemeier V (eds) Proceedings of the 16th international conference on finite elements in flow problems, Munich, p 127

    Google Scholar 

  68. Qamar A, Sanghi S (2009) Steady supersonic flow-field predictions using proper orthogonal decomposition technique. Comput Fluids 38:1218–1231

    Article  MATH  Google Scholar 

  69. Quagliarella D, Vicini A (2001) Viscous single and multicomponent airfoil design with genetic algorithms. Finite Elem Anal Des 37:365–380

    Article  MATH  Google Scholar 

  70. Rambo J, Joshi Y (2007) Reduced-order modeling of turbulent forced convection with parametric conditions. Int J Heat Mass Transf 50:539–551

    Article  MATH  Google Scholar 

  71. Ravindran S (2007) Optimal boundary feedback flow stabilization by model reduction. Comput Methods Appl Mech Eng 196:2555–2569

    Article  MathSciNet  MATH  Google Scholar 

  72. Renner G, Ekárt A (2003) Genetic algorithms in computer aided design. Comput Aided Des 35:709–726

    Article  Google Scholar 

  73. Rowley CW, Colonius T, Murray RM (2004) Model reduction for compressible flows using POD and Galerkin projection. Physica D 189:115–129

    MathSciNet  MATH  Google Scholar 

  74. Saino N, Rubolini D, Lehikoinen E, Sokolov L, Bonisoli-Alquati A, Ambrosini R, Boncoraglio G, Møller A (2009) Climate change effects on migration phenology may mismatch brood parasitic cuckoos and their hosts. Biol Lett 5(4):539–541

    Article  Google Scholar 

  75. Salimi H, Giveki D, Soltanshahi MA, Hatami J (2012) Extended mixture of MLP experts by hybrid of conjugate gradient method and modified cuckoo search. Int J Artif Intell Appl 3

  76. Sazonov I, Hassan O, Morgan K, Weatherill NP (2006) Smooth Delaunay–Voronoi dual meshes for co-volume integration schemes. In: Rebay PP (ed) Proceedings of the 15th international meshing roundtable. Springer, Berlin, pp 529–541

    Chapter  Google Scholar 

  77. Sazonov I, Hassan O, Morgan K, Weatherill NP (2007) Generating the Voronoi–Delaunay dual diagram for co-volume integration schemes. In: Gold CM (ed) 4th international symposium on Voronoï diagrams in science and engineering. IEEE Comput Soc, Los Alamitos, pp 199–204

    Chapter  Google Scholar 

  78. Sazonov I, Wang D, Hassan O, Morgan K, Weatherill N (2006) A stitching method for the generation of unstructured meshes for use with co-volume solution techniques. Comput Methods Appl Mech Eng 195:1826–1845

    Article  MathSciNet  MATH  Google Scholar 

  79. Selvi G, Purusothaman T (2012) Cryptanalysis of simple block ciphers using extensive heuristic attacks. Eur J Sci Res 78:198–221

    Google Scholar 

  80. Shatnawi M, Nasrudin MF (2011) Starting configuration of cuckoo search algorithm using centroidal Voronoi tessellations. In: 11th international conference on hybrid intelligent systems, Melacca

    Google Scholar 

  81. Speed ER (2010) Evolving a Mario agent using cuckoo search and softmax heuristics. In: Proceedings of games innovations conference (ICE-GIC), pp 1–7. doi:10.1109/ICEGIC.2010.5716893

    Google Scholar 

  82. Storn R, Price K (1997) Differential evolution—a simple and efficient heuristic for global optimization over continuous spaces. J Glob Optim 11:341–359

    Article  MathSciNet  MATH  Google Scholar 

  83. Tabib MV, Joshi JB (2008) Analysis of dominant flow structures and their flow dynamics in chemical process equipment using snapshot proper orthogonal decomposition technique. Chem Eng Sci 63:3695–3715

    Article  Google Scholar 

  84. Utturkar Y, Zhang B, Shyy W (2005) Reduced-order description of fluid flow with moving boundaries by proper orthogonal decomposition. Int J Heat Fluid Flow 26:276–288

    Article  Google Scholar 

  85. Vassberg JC, Jameson A (2002) Aerodynamic shape optimization of a Reno race plane. Int J Veh Des 28:318–338

    Article  Google Scholar 

  86. Vazquez RA (2011) Training spiking neural models using cuckoo search algorithm. In: 2011 IEEE congress on evolutionary computation

    Google Scholar 

  87. Viswanathan GM (2008) Lévy flights and superdiffusion in the context of biological encounters and random searches. Phys Life Rev 5:133–150

    Article  MathSciNet  Google Scholar 

  88. Walton S (2011) Open source project. http://code.google.com/p/modified-cs/

  89. Walton S, Hassan O, Morgan K (2013) Reduced order mesh optimisation using proper orthogonal decomposition and a modified cuckoo search. Int J Numer Methods Eng 93(5):527–550. doi:10.1002/nme.4400

    Article  MathSciNet  Google Scholar 

  90. Walton S, Hassan O, Morgan K, Brown MR (2011) Modified cuckoo search: a new gradient free optimisation algorithm. Chaos Solitons Fractals 44(9):710–718

    Article  Google Scholar 

  91. Wang Y, Yu B, Cao Z, Zou W, Yu G (2012) A comparative study of pod interpolation and pod projection methods for fast and accurate prediction of heat transfer problems. Int J Heat Mass Transf 55(17–18):4827–4836. doi:10.1016/j.ijheatmasstransfer.2012.04.053

    Article  Google Scholar 

  92. Weatherill NP, Hassan O (1994) Efficient three-dimensional Delaunay triangulation with automatic point creation and imposed boundary constraints. Int J Numer Methods Eng 37:2005–2040

    Article  MATH  Google Scholar 

  93. Weyland D (2010) A rigorous analysis of the harmony search algorithm—how the research community can be misled by a “novel” methodology. Int J Appl Metaheuristic Comput 1–2:50–60

    Article  Google Scholar 

  94. Wolpert D, Macready W (1997) No free lunch theorems for optimization. IEEE Trans Evol Comput 1:67–82

    Article  Google Scholar 

  95. Xie ZQ, Hassan O, Morgan K (2011) Tailoring unstructured meshes for use with a 3d time domain co-volume algorithm for computational electromagnetics. Int J Numer Methods Eng 87(1–5):48–65. doi:10.1002/nme.2970

    Article  MathSciNet  MATH  Google Scholar 

  96. Yang XS, Deb S (2009) Cuckoo search via Lévy flights. In: Proceedings of world congress on nature & biologically inspired computing (NaBIC 2009. IEEE Publications, Piscataway, pp 210–214

    Chapter  Google Scholar 

  97. Yang XS, Deb S (2010) Engineering optimisation by cuckoo search. Int J Math Model Numer Optim 1:330–343

    MATH  Google Scholar 

  98. Yee K (1966) Numerical solution of initial boundary value problems involving Maxwell’s equations in isotropic media. IEEE Trans Antennas Propag 14:302–307

    MATH  Google Scholar 

  99. Yildiz A (2013) Cuckoo search algorithm for the selection of optimal machining parameters in milling operations. Int J Adv Manuf Technol 64:55–61. doi:10.1007/s00170-012-4013-7

    Article  Google Scholar 

  100. Zimmermann R, Görtz S (2012) Improved extrapolation of steady turbulent aerodynamics using a non-linear POD-based reduced order model. Aeronaut J 116(1184):1079–1100

    Google Scholar 

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Walton, S., Hassan, O. & Morgan, K. Selected Engineering Applications of Gradient Free Optimisation Using Cuckoo Search and Proper Orthogonal Decomposition. Arch Computat Methods Eng 20, 123–154 (2013). https://doi.org/10.1007/s11831-013-9083-7

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